A DevOps team has a requirement for recovery of staging tables used in a complex set of data pipelines. The staging tables are all located in the same staging schema. One of the requirements is to have online recovery of data on a rolling 7-day basis. After setting up the DATA_RETENTION_TIME_IN_DAYS at the database level, certain tables remain unrecoverable past 1 day. What would cause this to occur? (Choose two.)
Correct Answer: B,D
* The DATA_RETENTION_TIME_IN_DAYS parameter controls the Time Travel retention period for an object (database, schema, or table) in Snowflake. This parameter specifies the number of days for * which historical data is preserved and can be accessed using Time Travel operations (SELECT, CREATE ... CLONE, UNDROP)1. * The requirement for recovery of staging tables on a rolling 7-day basis means that the DATA_RETENTION_TIME_IN_DAYS parameter should be set to 7 at the database level. However, this parameter can be overridden at the lower levels (schema or table) if they have a different value1. * Therefore, one possible cause for certain tables to remain unrecoverable past 1 day is that the DATA_RETENTION_TIME_IN_DAYS for the staging schema has been set to 1 day. This would override the database level setting and limit the Time Travel retention period for all the tables in the schema to 1 day. To fix this, the parameter should be unset or set to 7 at the schema level1. Therefore, option B is correct. * Another possible cause for certain tables to remain unrecoverable past 1 day is that the staging tables are of the TRANSIENT type. Transient tables are tables that do not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. Transient tables are suitable for temporary or intermediate data that can be easily reproduced or replicated2. To fix this, the tables should be created as permanent tables, which can have a Time Travel retention period of up to 90 days1. Therefore, option D is correct. * Option A is incorrect because the MANAGED ACCESS feature is not related to the data recovery requirement. MANAGED ACCESS is a feature that allows granting access privileges to objects without explicitly granting the privileges to roles. It does not affect the Time Travel retention period or the data availability3. * Option C is incorrect because there is no 1 TB limit for data recovery in Snowflake. The data storage size does not affect the Time Travel retention period or the data availability4. * Option E is incorrect because there is no ALLOW_RECOVERY privilege in Snowflake. The privilege required to perform Time Travel operations is SELECT, which allows querying historical data in tables5. References: : Understanding & Using Time Travel : Transient Tables : Managed Access : Understanding Storage Cost : Table Privileges
Question 92
Which of the below objects cannot be replicated from one region to the other?
Correct Answer: A,D
Question 93
Let's say that you have two JSONs as below 1. {"stuId":2000, "stuName":"Amy"} 2. {"stuId":2000,"stuCourse":"Snowflake"} How will you write a query that will check if stuId in JSON in #1 is also there in JSON in#2
Correct Answer: B,C
Question 94
What considerations apply when using database cloning for data lifecycle management in a development environment? (Select TWO).
Correct Answer: C,E
Zero-copy cloning in Snowflake creates a metadata-only snapshot of databases, schemas, or tables, enabling rapid environment refreshes without duplicating data. However, not all dependent objects behave identically during cloning. Pipes that reference external stages are not cloned because external stages depend on credentials and integrations that may not exist or be valid in the cloned environment (Answer C). This is a documented Snowflake behavior and an important consideration when cloning production environments into development. Regarding privileges, a cloned database inherits privileges granted on child objects (such as schemas and tables), but it does not inherit privileges granted directly on the source database itself (Answer E). This design prevents unintended access escalation and ensures that security must be explicitly re-granted at the database level. Understanding these nuances is essential for SnowPro Architect candidates when designing environment promotion strategies and managing data lifecycle processes using cloning. =========
Question 95
An Architect has selected the Snowflake Connector for Python to integrate and manipulate Snowflake data using Python to handle large data sets and complex analyses. Which features should the Architect consider in terms of query execution and data type conversion? (Select TWO).
Correct Answer: B,D
The Snowflake Connector for Python is designed to integrate Snowflake with Python-based analytics, ETL, and application workloads. One key capability is its support for both synchronous and asynchronous query execution, which allows architects to design scalable pipelines and applications that can submit long-running queries without blocking execution threads (Answer B). This is particularly important for large data sets and complex analytical workloads, where asynchronous execution improves throughput and application responsiveness. Additionally, the connector automatically converts Snowflake data types into native Python data types wherever possible (Answer D). For example, VARCHAR values are returned as Python strings, numeric values as Python numeric types, and timestamps as Python datetime objects. This default behavior simplifies downstream processing and analysis, eliminating the need for manual casting or parsing in most use cases. The connector does not convert all values to strings by default, nor does it specifically convert NUMBER to DECIMAL as a required behavior; instead, type conversion is handled intelligently to match Python equivalents. While cursors are used to execute queries, this is standard DB-API behavior and not a distinguishing feature for performance or architecture decisions. For SnowPro Architect candidates, understanding these connector capabilities is essential when designing Python-based data engineering or analytics solutions on Snowflake. =========
